Small and medium-sized enterprises (SMEs) in North Macedonia remain strongly dependent on bank credit, while many firms face “thin-file” constraints that limit access to finance. FinTech-enabled lending and alternative-data credit scoring offer the potential to expand credit supply by reducing information asymmetries and improving predictive accuracy, yet they also introduce legal, governance, and consumer-protection risks—especially around privacy, explainability, bias, and model risk management. This study develops a structured framework for evaluating alternative-data scoring models for SME credit in North Macedonia and derives regulatory implications aligned with European supervisory expectations. Using standards-based control mapping (EBA Guidelines on loan origination and monitoring; World Bank credit scoring guidance; IMF supervisory approaches; BIS research on privacy regulation), the paper proposes proportionate rules for data governance, transparency, and risk controls. The results indicate that alternative data can enhance inclusion and portfolio quality when integrated with robust governance, while weak oversight risks discriminatory outcomes and systemic vulnerabilities.